Assignment 8: Visualization - Making a bar race

How to do it?:

• Open the Rmarkdown file of this assignment (link) in Rstudio.

• Right under each question, insert a code chunk (you can use the hotkey Ctrl + Alt + I to add a code chunk) and code the solution for the question.

• Knit the rmarkdown file (hotkey: Ctrl + Alt + K) to export an html.

• Publish the html file to your Githiub Page.

Submission: Submit the link on Github of the assignment to Blackboard.

---

1. Install two packages gganimate and gifski then restart Rstudio. Use the WHO’s dataset at this link. Make a top-10 bar race by months between countries on the number of deaths by Covid 19.

library(gganimate)
library(gifski)
library(tidyverse)
library(lubridate)
library(ggplot2)
df <- read_csv("https://covid19.who.int/WHO-COVID-19-global-data.csv")

df$date <- ymd(df$Date_reported)
df$month <- month(df$date)
d1 <- df %>% group_by(month,Country) %>% summarise(mean = mean(Cumulative_deaths))
d2 <- d1 %>% group_by(month) %>% mutate(rank=rank(-mean)) %>% ungroup()
d3 <- d2 %>% filter(rank <= 10)

a1 <- d3 %>% ggplot(aes(x = rank, y = mean, group = Country, fill = Country, label = Country)) + geom_col() +
  geom_text(aes(y = mean, label = Country), hjust = 1.4) +
  coord_flip(clip = "off", expand = FALSE) + scale_x_reverse() +
  labs(title = 'Month {closest_state}', x = '', y = 'Total Number of Deaths', fill = 'country') +
  theme(plot.title = element_text(hjust = 1, size = 22),
        axis.ticks.y = element_blank(),
        axis.text.y = element_blank()) +
  transition_states(month)+
  ease_aes("cubic-in-out")

animate(a1, nframes = 400, fps = 10)

2. Make another bar race using that dataset.

df <- read_csv("https://covid19.who.int/WHO-COVID-19-global-data.csv")

df$date <- ymd(df$Date_reported)
df$month <- month(df$date)
d1 <- df %>% group_by(month,Country) %>% summarise(mean = mean(Cumulative_cases))
d2 <- d1 %>% group_by(month) %>% mutate(rank=rank(-mean)) %>% ungroup()
d3 <- d2 %>% filter(rank <= 10)

a1 <- d3 %>% ggplot(aes(x = rank, y = mean, group = Country, fill = Country, label = Country)) + geom_col() +
  geom_text(aes(y = mean, label = Country), hjust = 1.4) +
  coord_flip(clip = "off", expand = FALSE) + scale_x_reverse() +
  labs(title = 'Month {closest_state}', x = '', y = 'Total Number of Cases', fill = 'country') +
  theme(plot.title = element_text(hjust = 1, size = 22),
        axis.ticks.y = element_blank(),
        axis.text.y = element_blank()) +
  transition_states(month)+
  ease_aes("cubic-in-out")

animate(a1, nframes = 400, fps = 10)

3. Make a bar race using a dataset of your own interest. You may use the dataset that we use in class (https://covidtracking.com/data/download/all-states-history.csv) but you should make a different bar racev from ones in the slides.

df <- read_csv("https://covidtracking.com/data/download/all-states-history.csv")

df$date <- ymd(df$date)
df$month <- month(df$date)
d1 <- df %>% group_by(month,state) %>% summarise(mean = mean(death))
d2 <- d1 %>% group_by(month) %>% mutate(rank=rank(-mean)) %>% ungroup()
d3 <- d2 %>% filter(rank <= 10)

a1 <- d3 %>% ggplot(aes(x = rank, y = mean, group = state, fill = state, label = state)) + geom_col() +
  geom_text(aes(y = mean, label = state), hjust = 1.4) +
  coord_flip(clip = "off", expand = FALSE) + scale_x_reverse() +
  labs(title = 'Month {closest_state}', x = '', y = 'Total Number of Deaths', fill = 'state') +
  theme(plot.title = element_text(hjust = 1, size = 22),
        axis.ticks.y = element_blank(),
        axis.text.y = element_blank()) +
  transition_states(month)+
  ease_aes("cubic-in-out")

animate(a1, nframes = 400, fps = 10)

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